Elizabeth Stone

Their words

So looking at some of the code that some of these models or agents are writing they're very hard to follow. It's like I know I'm getting better performance from this but I have no idea why and if this thing breaks I'm going to have no idea how to fix it.

Their words

I think there's a difference between being able to write lines of code in a particular language like Python or C++ and understanding how code, computer systems, products work. And I don't think the latter is going away.

Their words

So, even in a world of AI where some things are easier, we were talking earlier about mindset, AI fluency. From my experience, younger folks are more open-minded. They tend to be more native in some of these new ways of working.

Their words

It does feel like we have to be more more explicit about the types of people and talent that tend to thrive at Netflix versus other companies like some of the frontier labs.

Their words

Or the perfect way to go through feedback and leveling and compensation. But every time we saw that and we added more process, we spent more time without getting better outcomes.

Their words

Well, the talent density is the non-negotiable. Like you have to start with that. If you don't have that, you can't get to a place where you have confidence in decision-making at all levels of the organization, allowing people to take risks and innovate quickly.

Their words

It was instead a very strongly held opinion that that you get to excellence by giving people a lot of agency and accountability. By pushing decisions as deep in the organization as possible, hiring great people who can be trusted to have good judgment and make good decisions.

Their words

And even for things like coding interviews, allowing candidates, of course, to use AI tools because that's going to be part of what the work requires now.

Their words

So, the most useful thing is not to make it level specific or role specific, but to encourage everyone towards the expectation on AI fluency, which doesn't mean use it as a tech for the sake of tech. It's tech where it's useful, to have good judgment about that, and to have the mindset to be open-minded to explore and try new things.

Their words

But as a general rule, uh compared to 5 or 10 years ago, I I would believe we have fewer specialists and more people who are generalists or adaptable in multiple directions.

Their words

But I think it would be a mistake to say design and deep design expertise and thinking gets squeezed out just because we can write code faster. We can do data analysis faster.

Their words

I get really nervous about having different design languages or different types of user interactions and shipping Frankensteins, basically. So, designers need to then be the people we're hiring again for design systems thinking.

Their words

In a world of AI with agents operating across multiple systems, wanting source of truth data, the importance of having preferred paved paths that get the most of the benefits and produce some guardrails so we can make sure we're doing good work, common infrastructure, common paved paths, solving problems once with a core set of capabilities becomes more important.

Their words

So, we are hiring more people who can look across all the business domains and abstract that to here's the building blocks we're going to need in a world with AI.

Their words

I still see a craft excellence that's really important in the disciplines that I don't think is going away anytime soon. Even if there's fluidity or blurring of the work across the functional lines.

Their words

Do I believe that means anyone should be shipping code to production? That everyone should actually be doing everything? Probably not. But I think that it's good for people to be exploring what's possible.

Their words

I think anytime a new technology comes along, especially one that's as transformative as GenAI, you go through a storming phase before you go through the forming phase of things. And I think we are in the middle of that right now.